Outsmarting, Not Outspending

Ask people whether they mostly bought healthy groceries during their last supermarket trip and many will say yes. Ask to see the receipt, however, and what ended up in the shopping cart often tells a different story. Why do people behave differently from what they report in surveys? Behavioral science has been trying to answer that question for decades.

Understanding why people make the decisions they do is fundamental to effective marketing. But behavioral science only creates value when its insights are translated into action. More recently, artificial intelligence has helped accelerate that process by uncovering the unconscious drivers behind decisions and turning them into clear, actionable recommendations.

Our solution is called Behave.AI. It is part of our House of AI and sits within our Insight.AI portfolio (alongside Research.AI, Persona.AI and Touchpoint.AI). Within our strategy, the roles of humans and machines are clearly defined: behavioral scientists frame the right questions, select the appropriate methodology and interpret the results, while AI supports the process through scoring, profiling and pattern recognition.

The challenge marketers face today is not a lack of data. Most organizations already have more than enough datasets and dashboards. The real challenge is turning that information into insights that lead to action. Marketing success ultimately depends on understanding the motives, triggers and decision factors that drive behavior. This is where AI can make a meaningful contribution.

Traditional media planning has often been based on reach and frequency. The more a brand spends, the more market impact it can generate. Historically, this outspending approach often worked. But the brands succeeding today are not necessarily those spending the most. They are the ones targeting more intelligently. AI-powered behavioral science supports this shift by delivering recommendations grounded in the motivations and decision-making mechanisms that actually influence behavior.

A recent project shows how Behave.AI can uncover new ways to engage an especially hard-to-reach audience: B2B decision-makers in the energy sector. To understand what shapes their choices, we analyzed this target group across six different markets.

A traditional audience profile might have looked something like this: predominantly male (60 percent), between 35 and 44 years old, above-average income, employed full-time and often working in industries such as oil, gas or mining.

What that profile does not tell us is where these people get their information, how they process it, how they assess risk or how they respond to signals from governments, institutions and the wider public.

Instead of relying on a single average persona, Behave.AI identified segments based on how decision-makers process information and evaluate risk. As a result, two individuals with almost identical demographic characteristics may belong to entirely different behavioral segments. Journalists and policymakers, for example, are not decision-makers in the strict sense, but they can significantly influence decisions through the signals they send.

One particularly interesting finding was that people in the “Energy Transition” and “Digital Infrastructure” segments were significantly more likely to consult large language models during the initial research phase. Their counterparts in more traditional industrial segments, meanwhile, were more likely to rely on specialist publications and review platforms.

For each market, we then developed a profile of the decision heuristics shaping behavior. This made it possible to identify which messages resonate in which markets and through which channels. A comparison between the United States and Germany illustrates the point:

Both markets place a high degree of trust in authority and expertise. What differs is what that authority is expected to deliver. In the United States, authority is expected to reinforce an existing viewpoint and provide quick proof points. In Germany, its primary role is to reduce risk and create certainty.

In the U.S., decision-makers tend to seek information that confirms their perspective and place considerable trust in established sources. For communicators, this means emphasizing proof over promises, credibility over claims and strong partner credentials. From a media perspective, these audiences are most effectively reached through digital channels, direct outreach and formats that allow proof points and references to be communicated clearly. The key drivers are confirmation-seeking behavior and a desire for visible, near-term results.

German decision-makers, by contrast, tend to favor proven solutions, clearly defined processes and risk mitigation. They look for validated data, expert endorsement and reassurance that the likelihood of making the wrong decision is as low as possible. As a result, communications should focus on validation, precision and reliability, particularly when it comes to delivery and timelines. Trade media plays a particularly important role here because it provides exactly the kind of expert authority German decision-makers rely on when evaluating options.

The central recommendation was therefore clear: avoid a one-size-fits-all global campaign. Markets differ too significantly in how decisions are made. Instead, organizations should develop market-specific and segment-specific messaging and channel strategies based on decision behavior rather than demographics alone.

This case illustrates how Behave.AI can help evolve media strategy from demographic targeting to personalized, behavior-based engagement. The next generation of media planning is no longer simply data-driven. It is intelligence-driven.